FROM nvidia/cuda:9.0-base-ubuntu16.04 LABEL maintainer="Craig Citro " RUN apt-get update && apt-get install -y --no-install-recommends \ build-essential \ cuda-command-line-tools-9-0 \ cuda-cublas-dev-9-0 \ cuda-cudart-dev-9-0 \ cuda-cufft-dev-9-0 \ cuda-curand-dev-9-0 \ cuda-cusolver-dev-9-0 \ cuda-cusparse-dev-9-0 \ curl \ git \ libcudnn7=7.2.1.38-1+cuda9.0 \ libcudnn7-dev=7.2.1.38-1+cuda9.0 \ libnccl2=2.2.13-1+cuda9.0 \ libnccl-dev=2.2.13-1+cuda9.0 \ libcurl3-dev \ libfreetype6-dev \ libhdf5-serial-dev \ libpng12-dev \ libzmq3-dev \ pkg-config \ python-dev \ rsync \ software-properties-common \ unzip \ zip \ zlib1g-dev \ wget \ && \ rm -rf /var/lib/apt/lists/* && \ find /usr/local/cuda-9.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete && \ rm /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a RUN apt-get update && \ apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda9.0 && \ apt-get update && \ apt-get install libnvinfer4=4.1.2-1+cuda9.0 && \ apt-get install libnvinfer-dev=4.1.2-1+cuda9.0 # Link NCCL libray and header where the build script expects them. RUN mkdir /usr/local/cuda-9.0/lib && \ ln -s /usr/lib/x86_64-linux-gnu/libnccl.so.2 /usr/local/cuda/lib/libnccl.so.2 && \ ln -s /usr/include/nccl.h /usr/local/cuda/include/nccl.h RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py && \ python get-pip.py && \ rm get-pip.py RUN pip --no-cache-dir install \ Pillow \ h5py \ ipykernel \ jupyter \ keras_applications \ keras_preprocessing \ matplotlib \ mock \ numpy \ scipy \ sklearn \ pandas \ && \ python -m ipykernel.kernelspec # RUN ln -s -f /usr/bin/python3 /usr/bin/python# # Set up our notebook config. COPY jupyter_notebook_config.py /root/.jupyter/ # Jupyter has issues with being run directly: # https://github.com/ipython/ipython/issues/7062 # We just add a little wrapper script. COPY run_jupyter.sh / # Set up Bazel. # Running bazel inside a `docker build` command causes trouble, cf: # https://github.com/bazelbuild/bazel/issues/134 # The easiest solution is to set up a bazelrc file forcing --batch. RUN echo "startup --batch" >>/etc/bazel.bazelrc # Similarly, we need to workaround sandboxing issues: # https://github.com/bazelbuild/bazel/issues/418 RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone" \ >>/etc/bazel.bazelrc # Install the most recent bazel release. ENV BAZEL_VERSION 0.15.0 WORKDIR / RUN mkdir /bazel && \ cd /bazel && \ curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \ curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE && \ chmod +x bazel-*.sh && \ ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \ cd / && \ rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh # Download and build TensorFlow. WORKDIR /tensorflow RUN git clone --branch=r1.11 --depth=1 https://github.com/tensorflow/tensorflow.git . # Configure the build for our CUDA configuration. ENV CI_BUILD_PYTHON python ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH ENV TF_NEED_CUDA 1 ENV TF_NEED_TENSORRT 1 ENV TF_CUDA_COMPUTE_CAPABILITIES=3.5,5.2,6.0,6.1,7.0 ENV TF_CUDA_VERSION=9.0 ENV TF_CUDNN_VERSION=7 # NCCL 2.x ENV TF_NCCL_VERSION=2 RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 && \ LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs:${LD_LIBRARY_PATH} \ tensorflow/tools/ci_build/builds/configured GPU \ bazel build -c opt --copt=-mavx --config=cuda \ --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" \ tensorflow/tools/pip_package:build_pip_package && \ rm /usr/local/cuda/lib64/stubs/libcuda.so.1 && \ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip && \ pip --no-cache-dir install --upgrade /tmp/pip/tensorflow-*.whl && \ rm -rf /tmp/pip && \ rm -rf /root/.cache # Clean up pip wheel and Bazel cache when done. WORKDIR /root # TensorBoard EXPOSE 6006 # IPython EXPOSE 8888